We’ve all heard the canned notifications when we call companies for customer service: “this call may be recorded for security or quality purposes.” Most customer service organizations today record their phone interactions with their customers. Often those recordings just sit untouched on the digital equivalent of a dusty shelf in a storage closet. The recordings are there to ensure regulatory compliance or, in rare cases, to be pulled off the shelf in case of a major dispute with a customer. In essence, the part of the notification about security rings true; the quality part, not so much.

But, as part of continuous improvement programs, companies have begun to change that by actually analyzing the recordings for quality purposes. That process of quality monitoring allows firms to select recordings for review and assessment. In forward-thinking organizations, the tools enable managers to replay agent screen actions, allowing evaluations to include screen activity in addition to voice content. Managers use these reviews to pinpoint which agents perform well, which need further training, and to identify processes that need to be refined.

Companies doing this basic form of quality monitoring, however, find they cannot change the outcome of those calls — the interactions are long since over. This is where the emerging field of real-time speech analytics comes into play. Vendors of real-time speech analytics tools promise to allow companies to intervene at the moment of truth, while the customer and the contact center agent are still talking.

Customers and companies would both benefit from systems that identify which ongoing customer phone calls were going very badly or which agents were not complying with regulatory requirements. Real-time speech analytics can provide companies actionable advice on how to fix those issues. The ability to use real-time speech analytics to present agents the best upsell offer for that specific customer could also generate tangible revenues for brands.

If only it were that simple. Due to the intensive processing power required to spot emergent problems or opportune cross-sell moments in a phone call, the current crop of real-time speech analytics tools is expensive when used at scale. Additionally, the tools require ongoing tuning to remain effective post-deployment.

Our new research piece, “Real-Time Speech Analytics — Still More Sizzle Than Steak,”covers the hurdles customer service pros will need to overcome to justify the cash outlay on this technology and five practical steps they should to take to prepare for a world of alerts generated in real-time based on customer conversations.